Constraint Intelligence for AI Agents
An agent can decide what it wants to do. An operational system still needs to decide whether that action fits policy, capacity, permissions, timing, and dependencies.
Navokoj sits at that boundary.
The control loop
An agent proposes an action. The application turns the proposal and the current state into a constraint model. Navokoj evaluates admissibility, identifies conflicts, and returns either an executable assignment or a structured reason to revise the proposal.
This is more useful than a binary guardrail when the world is constrained but not completely impossible. The runtime can preserve mandatory rules while suggesting the closest workable alternative for the preferences that no longer fit.
Where it helps
The pattern applies to deployment changes, refunds, access requests, cloud placement, procurement, and scheduling. The agent remains responsible for intent. The constraint runtime makes the operational boundary explicit.
The result is not “the model said yes.” It is a decision record with the input, deadline, outcome, residual conflicts, and verification metadata.